Analysis of Qualcomms AI Technologies, Patents, and Strategies
With a successful business model, Qualcomm has dominated the CDMA (Code Division Multiple Access), 3G EV-DO (Evolution-Data Optimized), and 4G LTE (Long Term Evolution) baseband markets. But success comes with hidden worries. The company’s excessive focus on the mobile phone market has led to a decline in its revenue and patent royalty. Therefore, Qualcomm has tried to transform its business and drive sustainable growth through strategic investments in the development of emerging applications, acquisitions, and technologies and patents. These efforts, especially the emerging application markets that Qualcomm’s AI (Artificial Intelligence) technology has aimed at, provide important clues for understanding Qualcomm’s deployment plans. This report looks into what core AI technologies Qualcomm has focused on and examines smart applications that Qualcomm’s AI technology has been applied to.
1. BACKGROUND
2. PATENT DISTRIBUTION ANALYSIS
2.1 Patent Mining
2.2 Patent Analysis
2.2.1 Analysis by Field
2.2.2 Analysis by Core Technologies
2.2.3 Analysis by Smart Applications
2.2.4 Matrix Analysis of Core AI Technologies and Smart Applications
3. INVESTMENT PROJECTS ANALYSIS
4. ACQUISITION PROJECTS ANALAYSIS
5. CONCLUSIONS
5.1 Qualcomm Facing Revenue Dilemmas Due to Excessive Focus on Mobile Phone Market
5.2 Investment Focuses on Machine Learning Solutions for Car Electronics, Healthcare, Medical Technology, and Robot Applications
5.3 Core AI Patents Focus on Neural Networks and Natural Language Processing While Machine Learning Patents on the Rise
5.4 Communications Patents Account for Largest Share in AI Applications, Followed by Neuromorphic Computing Hardware, Transport, Healthcare, and Medical Technology
Appendix
Glossary of Terms
List of Companies
2. PATENT DISTRIBUTION ANALYSIS
2.1 Patent Mining
2.2 Patent Analysis
2.2.1 Analysis by Field
2.2.2 Analysis by Core Technologies
2.2.3 Analysis by Smart Applications
2.2.4 Matrix Analysis of Core AI Technologies and Smart Applications
3. INVESTMENT PROJECTS ANALYSIS
4. ACQUISITION PROJECTS ANALAYSIS
5. CONCLUSIONS
5.1 Qualcomm Facing Revenue Dilemmas Due to Excessive Focus on Mobile Phone Market
5.2 Investment Focuses on Machine Learning Solutions for Car Electronics, Healthcare, Medical Technology, and Robot Applications
5.3 Core AI Patents Focus on Neural Networks and Natural Language Processing While Machine Learning Patents on the Rise
5.4 Communications Patents Account for Largest Share in AI Applications, Followed by Neuromorphic Computing Hardware, Transport, Healthcare, and Medical Technology
Appendix
Glossary of Terms
List of Companies
LIST OF TABLES
Table 1 Development of Qualcomm's Core AI Technologies
Table 2 Smart Application Areas of Qualcomm's AI Technologies
Table 3 Matrix Analysis of Qualcomm's Core AI Technologies and Smart Applications
Table 4 Qualcomm Ventures' Investment between 2013 and 2017
Table 5 Qualcomm's M&A between 2013 and 2017
Table 1 Development of Qualcomm's Core AI Technologies
Table 2 Smart Application Areas of Qualcomm's AI Technologies
Table 3 Matrix Analysis of Qualcomm's Core AI Technologies and Smart Applications
Table 4 Qualcomm Ventures' Investment between 2013 and 2017
Table 5 Qualcomm's M&A between 2013 and 2017
LIST OF FIGURES
Figure 1 Qualcomm's Business Model
Figure 2 Qualcomm's Revenue Structure, 2012 - 2016
Figure 3 Qualcomm's AI Patent Distribution Share by Field
Figure 1 Qualcomm's Business Model
Figure 2 Qualcomm's Revenue Structure, 2012 - 2016
Figure 3 Qualcomm's AI Patent Distribution Share by Field
